Buscar en Google Scholar
Título: Corn crops identification using multispectral images from unmanned aircraft systems
Asesor(es): Racoceanu, Daniel
Campo OCDE: https://purl.org/pe-repo/ocde/ford#2.02.05
Fecha de publicación: 8-abr-2019
Institución: Pontificia Universidad Católica del Perú
Resumen: Climate change and migration of population from rural to urban areas are affecting the agricultural production around the world. This study was based in the particular department of Ancash - Peru where corn is one of the most important crops of the region. Authorities in this region are concerned in finding a method, different from census; that can constantly monitor corn crops areas. This data is important to evaluate how these two causes will impact on food security in Ancash. The first part of the present thesis reviews the current techniques in the recognition of crop areas using remote sensing and multispectral images. The second part explains the methodology developed for this study, considering the data acquisition using Unmanned Aircraft Systems, the preparation of the acquired data and two deep learning model approaches. The first approach is based on binary classification of corn patches using Le Net model with near infrared images. The second one describes the segmentation of corn areas in different stages using the U-net model, in this case five band images were considered. The third part shows the results of both approaches. From these results it is concluded that training a model with data from different stages and scenarios of two campaigns (2016 and 2017) can achieve a 95% of accuracy in corn segmentation.
Disciplina académico-profesional: Procesamiento de Señales e Imágenes Digitales
Institución que otorga el grado o título: Pontificia Universidad Católica del Perú. Escuela de Posgrado
Grado o título: Maestro en Procesamiento de Señales e Imágenes Digitales.
Fecha de registro: 8-abr-2019; 8-abr-2019



IMPORTANTE
La información contenida en este registro es de entera responsabilidad de la universidad, institución o escuela de educación superior que administra el repositorio académico digital donde se encuentra el trabajo de investigación y/o proyecto, los cuales son conducentes a optar títulos profesionales y grados académicos. SUNEDU no se hace responsable por los contenidos accesibles a través del Registro Nacional de Trabajos de Investigación – RENATI.